CN109655903A - Rammell S-Wave Velocity Predicted Method and system - Google Patents
Rammell S-Wave Velocity Predicted Method and system Download PDFInfo
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- CN109655903A CN109655903A CN201710942514.2A CN201710942514A CN109655903A CN 109655903 A CN109655903 A CN 109655903A CN 201710942514 A CN201710942514 A CN 201710942514A CN 109655903 A CN109655903 A CN 109655903A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/303—Analysis for determining velocity profiles or travel times
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/622—Velocity, density or impedance
- G01V2210/6222—Velocity; travel time
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/66—Subsurface modeling
Abstract
The invention discloses a kind of rammell S-Wave Velocity Predicted Method and systems, which includes: step 1: explaining acquisition log parameter to log data；Step 2: being based on log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio initial value and clay mineral directional index initial value；Step 3: being based on porosity aspect ratio initial value, clay mineral directional index initial value and shale anisotropic rock physical model, obtain velocity of longitudinal wave, shear wave velocity and density；Step 4: being based on objective function, judge whether velocity of longitudinal wave, shear wave velocity and density meet the requirements.The rammell S-Wave Velocity Predicted Method can accurately predict shale gas reservoir shear wave velocity.
Description
Technical field
The invention belongs to shale gas and shale oil seismic prospecting and development technique fields, more particularly, to a kind of shale
Layer S-Wave Velocity Predicted Method and system.
Background technique
Prestack seismic data inverting can provide predictive information related with formation lithology, physical property and oil-gas possibility, horizontal
Wave velocity has very important effect in Prestack seismic data inverting and AVO attributive analysis, combines longitudinal wave and shear wave letter
Breath helps to reduce the uncertainty of reservoir prediction, improves the precision of shale gas dessert identification.But in practice, s-wave logging because
Its is at high cost, and a work area only has a small number of wells to have shear wave logging data, even without shear wave logging data.Therefore by log data
Predict that it is very important to reservoir prediction for shear wave velocity.
S-Wave Velocity Predicted Method based on rock physics theory is the main means for predicting shear wave velocity, and many scholars are logical
Cross Petrophysical measurement, it is intended to establish the empirical relation between P- and S-wave velocity, or by petrophysical model by known longitudinal wave
Speed and other reservoir parameters, such as shale content, porosity estimate shear wave velocity.For conventional crumb rock and carbonate rock
The empirical equation and theoretical model that stratum is established are not applicable to shale gas reservoir, and are directed to shale gas reservoir rock physical modeling
And its research of shear wave velocity prediction is less.In addition, in terms of shear wave velocity prediction, it is also desirable to establish accurate rock physics mould
Type, and current shale petrophysical model not yet fully considers the mineral constituent and microstructure of shale complexity, and ignores more
Its strong anisotropic character and its influence factor etc., so that the applicability of method and shear wave velocity precision of prediction are difficult to meet reality
Border demand.The shear wave velocity prediction for how carrying out shale gas reservoir has become a technical problem of this field.
The rammell shear wave velocity that can accurately predict shale gas reservoir shear wave velocity therefore, it is necessary to develop one kind is pre-
Survey method and system.
Summary of the invention
The invention proposes a kind of rammell S-Wave Velocity Predicted Method and system, the rammell S-Wave Velocity Predicted Methods
It can accurately predict shale gas reservoir shear wave velocity.
To achieve the goals above, a kind of rammell S-Wave Velocity Predicted Method is provided according to an aspect of the present invention,
This method comprises:
Step 1: acquisition log parameter is explained to log data；
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio
Initial value and clay mineral directional index initial value；
Step 3: being based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale
Anisotropic rock physical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet and want
It asks；
In the case where being unsatisfactory for requirement, pore components are updated by Monte Carlo optimization algorithm and clay mineral orientation refers to
Number repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, inverting obtains hole
Degree when clay mineral directional index in length and breadth, based on porosity, when clay mineral directional index passes through shale anisotropy in length and breadth
Petrophysical model obtains prediction shear wave velocity value.
Preferably, the step 4 includes: to calculate square error by objective function, to the square error given threshold,
It is judged to being unsatisfactory for requiring when square error is greater than the threshold value, sentences when the square error is less than or equal to the threshold value
It is set to and meets the requirements；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；Deni
For the density of log data actual measurement, Den’ iThe density data calculated for this method；N is total number of samples of log data, and i is sampling point
Serial number.
Preferably, further include step 5: to determining that number sets frequency threshold value, when determining that number is more than frequency threshold value, and it is flat
When square error is greater than threshold value, explanation is optimized based on log data, obtains new log parameter, repeats step 2 to step 4.
Preferably, which is characterized in that further include step 6: step 1 being executed to step 5 to all logging points, obtains rammell
Section shear wave velocity prediction curve.
Preferably, building shale anisotropic rock physical model includes: that shale matrix is considered as brittle mineral, organic matter
With the mixture of clay composition；Clay particle is considered as the anisotropic element with the elastic stiffness matrix that immobilizes, is introduced viscous
Native mineral directional index characterization clay mineral aligns degree；Total pore space is divided into brittleness hole, clay hole and organic matter hole,
The addition in brittle mineral hole and organic matter hole uses DEM model, and the addition of clay mineral hole uses anisotropy DEM model；
The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, clay and mixture 1 (brittle mineral and organic matter
Mixture) mixing use anisotropy SCA-DEM model；It is replaced and is managed using Brown-Korringa anisotropic fluid
By saturated with fluid shale Equivalent Elasticity tensor being obtained by dry rock Equivalent Elasticity tensor, to set up shale anisotropy rock
Stone physical model.
A kind of rammell shear wave velocity forecasting system is provided according to another aspect of the present invention, comprising:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Step 1: acquisition log parameter is explained to log data；
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio
Initial value and clay mineral directional index initial value；
Step 3: being based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale
Anisotropic rock physical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet and want
It asks；
In the case where being unsatisfactory for requirement, pore components are updated by Monte Carlo optimization algorithm and clay mineral orientation refers to
Number repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, inverting obtains hole
Degree when clay mineral directional index in length and breadth, based on porosity, when clay mineral directional index passes through shale anisotropy in length and breadth
Petrophysical model obtains prediction shear wave velocity value.
Preferably, the step 4 includes: to calculate square error by objective function, to the square error given threshold,
It is judged to being unsatisfactory for requiring when square error is greater than the threshold value, sentences when the square error is less than or equal to the threshold value
It is set to and meets the requirements；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；Deni
For the density of log data actual measurement, Den 'iThe density data calculated for this method；N is total number of samples of log data, and i is sample
Point serial number.
Preferably, further include step 5: to determining that number sets frequency threshold value, when determining that number is more than frequency threshold value, and it is flat
When square error is greater than threshold value, explanation is optimized based on log data, obtains new log parameter, repeats step 2 to step 4.
Preferably, further include step 6: step 1 being executed to step 5 to all logging points, obtains shale interval shear wave velocity
Prediction curve.
Preferably, building shale anisotropic rock physical model includes: that shale matrix is considered as brittle mineral, organic matter
With the mixture of clay composition；Clay particle is considered as the anisotropic element with the elastic stiffness matrix that immobilizes, is introduced viscous
Native mineral directional index characterization clay mineral aligns degree；Total pore space is divided into brittleness hole, clay hole and organic matter hole,
The addition in brittle mineral hole and organic matter hole uses DEM model, and the addition of clay mineral hole uses anisotropy DEM model；
The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, clay and mixture 1 (brittle mineral and organic matter
Mixture) mixing use anisotropy SCA-DEM model；It is replaced and is managed using Brown-Korringa anisotropic fluid
By saturated with fluid shale Equivalent Elasticity tensor being obtained by dry rock Equivalent Elasticity tensor, to set up shale anisotropy rock
Stone physical model.
The beneficial effects of the present invention are: rammell S-Wave Velocity Predicted Method of the invention, it will storage in modeling process
Layer hole be divided into brittle mineral hole, clay mineral hole and organic matter hole three parts, fully considered pore morphology and
The directionality of clay mineral influences, and is anisotropic rock physical model truly, so that modeling result is truer
Reliably；The present invention utilizes Monte Carlo optimization algorithm inverting pore components and clay directional index, and then predicts shear wave velocity,
The beneficial effect is that more preferable for domestic strong anisotropy shale formation applicability, shear wave velocity prediction result is more reasonable and quasi-
Really.The present invention is able to solve the problem of lacking the accurate prediction to shale gas-bearing formation shear wave velocity in the prior art.
Other features and advantages of the present invention will then part of the detailed description can be specified.
Detailed description of the invention
Exemplary embodiment of the invention is described in more detail in conjunction with the accompanying drawings, it is of the invention above-mentioned and its
Its purpose, feature and advantage will be apparent, wherein in exemplary embodiment of the invention, identical reference label
Typically represent same parts.
Fig. 1 shows the flow chart of rammell S-Wave Velocity Predicted Method according to an embodiment of the invention.
The well logging that Fig. 2 a- Fig. 2 f shows somewhere shale gas well interval of interest according to one embodiment of present invention is bent
Line schematic diagram.
Fig. 3 a- Fig. 3 f shows rammell S-Wave Velocity Predicted Method according to an embodiment of the invention and estimates to obtain
The comparison diagram of the shear wave velocity curve of somewhere shale gas well and actually measured shear wave velocity curve.
Specific embodiment
The preferred embodiment of the present invention is described in more detail below.Although the following describe preferred implementations of the invention
Mode, however, it is to be appreciated that may be realized in various forms the present invention without that should be limited by the embodiments set forth herein.Phase
Instead, these embodiments are provided so that the present invention is more thorough and complete, and can be by the scope of the present invention completely
It is communicated to those skilled in the art.
Embodiment 1
A kind of rammell S-Wave Velocity Predicted Method is provided according to an aspect of the present invention, this method comprises:
Step 1: acquisition log parameter is explained to log data.
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio
Initial value and clay mineral directional index initial value；
Step 3: being based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale
Anisotropic rock physical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet and want
It asks；
In the case where being unsatisfactory for requirement, pore components are updated by Monte Carlo optimization algorithm and clay mineral orientation refers to
Number repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, inverting obtains hole
Degree when clay mineral directional index in length and breadth, based on porosity, when clay mineral directional index passes through shale anisotropy in length and breadth
Petrophysical model obtains prediction shear wave velocity value.
The embodiment rammell S-Wave Velocity Predicted Method can accurately predict shale gas reservoir shear wave velocity.
The following detailed description of the specific steps of rammell S-Wave Velocity Predicted Method according to the present invention.
Step 1: acquisition log parameter is explained to log data.
Specifically, the log datas such as log data, including well depth, velocity of longitudinal wave, density, gamma are obtained；Obtain well logging solution
It releases as a result, including porosity, the content of organic matter, mineral constituent content and fluid saturation；Obtain mineral constituent, kerogen, hole
The elastic parameter and density of clearance flow body.
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio
Initial value and clay mineral directional index initial value.
In one example, building shale anisotropic rock physical model includes: that shale matrix etc. is considered as brittleness mine
The mixture of object, organic matter and clay composition；Clay particle etc., which is considered as, has each to different of elastic stiffness matrix that immobilize
Property member, introduce clay mineral directional index characterization clay mineral align degree；Total pore space is divided into brittleness hole, clay hole
With organic matter hole, the addition in brittle mineral hole and organic matter hole uses DEM model, and the addition of clay mineral hole is using each to different
Property DEM model；The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, clay and (the brittleness mine of mixture 1
The mixture of object and organic matter) mixing use anisotropy SCA-DEM model；Using Brown-Korringa Anisotropic-Flow
Body replacement is theoretical, saturated with fluid shale Equivalent Elasticity tensor is obtained by dry rock Equivalent Elasticity tensor, so that it is each to set up shale
Anisotropy petrophysical model.
Specifically, shale anisotropic rock physical model modeling method specifically include shale Rock Matrix modulus calculate,
The dry rock matrix modulus of shale calculates and shale saturated rock modulus calculates three big steps, sees shale matrix as brittleness mine
The mixture of object, organic matter and clay composition；Clay particle is considered as the anisotropy with the elastic stiffness matrix that immobilizes
Member introduces clay mineral directional index characterization clay mineral and aligns degree；By total pore space be divided into brittleness hole, clay hole and
Organic matter hole, the addition in brittle mineral hole and organic matter hole use DEM model, and the addition of clay mineral hole uses anisotropy
DEM model；The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, clay and 1 (brittle mineral of mixture
With the mixture of organic matter) mixing use anisotropy SCA-DEM model；Using Brown-Korringa anisotropic fluid
Replacement is theoretical, obtains saturated with fluid shale Equivalent Elasticity tensor by dry rock Equivalent Elasticity tensor, thus set up shale respectively to
Anisotropic petrophysical model.
Step 3: being based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale
Anisotropic rock physical model obtains velocity of longitudinal wave, shear wave velocity and density.
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet and want
It asks.
In the case where being unsatisfactory for requirement, pore components are updated by Monte Carlo optimization algorithm and clay mineral orientation refers to
Number repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, inverting obtains hole
Degree when clay mineral directional index in length and breadth, based on porosity, when clay mineral directional index passes through shale anisotropy in length and breadth
Petrophysical model obtains prediction shear wave velocity value.
Specifically, it is obtained using Monte Carlo optimization algorithm inverting pore components and clay directional index, specific method is such as
Under, for each logging point, set the pore components value interval of clay mineral as 0.001-1.000, step-length 0.001；
The value interval of the directional index of clay mineral is set as 0-1, step-length 0.001；It is calculated using petrophysical model traversal every
Velocity of longitudinal wave and density parameter in the case of one group of parameter.It seeks and stores the clay hole so that when objective function reaches minimum
The directional index of gap aspect ratio and clay mineral, the result of as final inverting.
In one example, the step 4 includes: to calculate square error by objective function, is set to the square error
Determine threshold value, be judged to being unsatisfactory for requiring when square error is greater than the threshold value, when the square error is less than or equal to described
It is judged to meeting the requirements when threshold value；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V’p0iThe velocity of longitudinal wave data calculated for this method；Deni
For the density of log data actual measurement, Den’ iThe density data calculated for this method；N is total number of samples of log data, and i is sampling point
Serial number.
It in one example, further include step 5: to number setting frequency threshold value is determined, when judgement number is more than number threshold
Value, and square error be greater than threshold value when, explanation is optimized based on log data, obtains new log parameter, repeat step 2 to
Step 4.
In one example, further include step 6: step 1 being executed to step 5 to all logging points, it is horizontal to obtain shale interval
Wave velocity prediction curve.
Embodiment 2
A kind of rammell shear wave velocity forecasting system is provided in another aspect of this invention, comprising:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Step 1: acquisition log parameter is explained to log data；
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, give porosity aspect ratio
Initial value and clay mineral directional index initial value；
Step 3: being based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale
Anisotropic rock physical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet and want
It asks；
In the case where being unsatisfactory for requirement, pore components are updated by Monte Carlo optimization algorithm and clay mineral orientation refers to
Number repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, inverting obtains hole
Degree when clay mineral directional index in length and breadth, based on porosity, when clay mineral directional index passes through shale anisotropy in length and breadth
Petrophysical model obtains prediction shear wave velocity value.
In one example, the step 4 includes: to calculate square error by objective function, is set to the square error
Determine threshold value, be judged to being unsatisfactory for requiring when square error is greater than the threshold value, when the square error is less than or equal to described
It is judged to meeting the requirements when threshold value；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；Deni
For the density of log data actual measurement, Den 'iThe density data calculated for this method；N is total number of samples of log data, and i is sample
Point serial number.
Specifically, threshold value be set as velocity of longitudinal wave and density quadratic sum 0.5% (threshold value can be according to the reality of work area data
Border situation adjusts, 1%) usual threshold value setting should be less than.Using measured data and this method calculate as a result, calculating target letter
Numerical value, that is, square error sum, if it is to meet the requirements that target function value, which is less than or equal to threshold value, if target function value is big
It is to be unsatisfactory for requiring in threshold value.
It in one example, further include step 5: to number setting frequency threshold value is determined, when judgement number is more than number threshold
Value, and square error be greater than threshold value when, explanation is optimized based on log data, obtains new log parameter, repeat step 2 to
Step 4.
Specifically, that the first step input in this method is log data and result of log interpretation (explaining parameter), we
Specific well logging and log interpretation technology are not included in method, when Optimal Parameters are all unable to reach setting anyway using this method
When threshold value, it is generally recognized that there may be problems for log data or result of log interpretation, and well log interpretation personnel is needed to go to verify at this time
Log data and result of log interpretation need to reinterpret log data in most cases.As to how to well logging number
It is explained according to optimizing, that is a very big subject and technical field, not in the column of the present invention.
In one example, further include step 6: step 1 being executed to step 5 to all logging points, it is horizontal to obtain shale interval
Wave velocity prediction curve.
In one example, building shale anisotropic rock physical model includes: that shale matrix etc. is considered as brittleness mine
The mixture of object, organic matter and clay composition；Clay particle etc., which is considered as, has each to different of elastic stiffness matrix that immobilize
Property member, introduce clay mineral directional index characterization clay mineral align degree；Total pore space is divided into brittleness hole, clay hole
With organic matter hole, the addition in brittle mineral hole and organic matter hole uses DEM model, and the addition of clay mineral hole is using each to different
Property DEM model；The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, clay and (the brittleness mine of mixture 1
The mixture of object and organic matter) mixing use anisotropy SCA-DEM model；Using Brown-Korringa Anisotropic-Flow
Body replacement is theoretical, saturated with fluid shale Equivalent Elasticity tensor is obtained by dry rock Equivalent Elasticity tensor, so that it is each to set up shale
Anisotropy petrophysical model.
Embodiment
Fig. 1 shows the flow chart of rammell S-Wave Velocity Predicted Method according to an embodiment of the invention.Fig. 2 a-
Fig. 2 f shows the log schematic diagram of somewhere shale gas well interval of interest according to one embodiment of present invention.Figure
3a- Fig. 3 f shows rammell S-Wave Velocity Predicted Method according to an embodiment of the invention and estimates to obtain somewhere shale
The comparison diagram of the shear wave velocity curve of gas well and actually measured shear wave velocity curve.
Shown in a- Fig. 2 f and Fig. 3 a- Fig. 3 f as shown in Figure 1, Figure 2, which includes: to obtain well logging
The log datas such as data, including well depth, velocity of longitudinal wave, density, gamma；Acquisition log parameter is explained to log data, is wrapped
Include porosity, the content of organic matter, mineral constituent content and fluid saturation；Obtain mineral constituent, kerogen, pore-fluid bullet
Property parameter and density parameter；Shale anisotropic rock physical model is constructed, total pore space is divided into brittle mineral hole, clay
Mineral hole and organic matter hole three parts；Objective function of the building for the prediction of constrained optimization shear wave；Given pore components
With the initial value of clay mineral directional index, velocity of longitudinal wave, shear wave speed are obtained by shale anisotropic rock physical model calculating
The initial predicted result and target function value of degree and density；It is fixed using Monte Carlo optimization algorithm inverting pore components and clay
To index, so that root-mean-square error defined in objective function is minimum, and the prediction of shear wave velocity is calculated by petrophysical model
As a result；Above-mentioned steps are executed to all well logging dot cycles, shale interval shear wave velocity prediction curve can be obtained.
Fig. 1 shows the flow chart of rammell S-Wave Velocity Predicted Method according to an embodiment of the invention.Such as Fig. 1
Shown, this method comprises the following steps:
1) log data (well depth, velocity of longitudinal wave, density, gamma etc.), result of log interpretation (porosity, organic matter are inputted
Content, mineral constituent content and fluid saturation etc.), the elastic parameters (speed, density, modulus or stiffness matrix) of mineral；
2) brittle mineral hole, clay hole and organic matter hole content are calculated by total porosity, and given clay hole is vertical
The horizontal initial value than with two parameters of clay mineral directional index；
3) construct shale anisotropic rock physical model, modeling method specifically include shale Rock Matrix modulus calculate,
The dry rock matrix modulus of shale calculates and shale saturated rock modulus calculates three big steps, method particularly includes: shale matrix is seen
Mixture as brittle mineral, organic matter and clay composition；Clay particle, which is considered as, has the elastic stiffness matrix that immobilizes
Anisotropic element, introduce clay mineral directional index characterization clay mineral align degree；Total pore space is divided into brittleness
The addition in hole, clay hole and organic matter hole, brittle mineral hole and organic matter hole uses DEM model, the addition of clay mineral hole
Using anisotropy DEM model；The mixing of brittle mineral and organic matter use isotropism SCA-DEM model, clay with mix
The mixing of object 1 (mixture of brittle mineral and organic matter) uses anisotropy SCA-DEM model；Using Brown-Korringa
Anisotropic fluid replacement is theoretical, saturated with fluid shale Equivalent Elasticity tensor is obtained by dry rock Equivalent Elasticity tensor, to build
Erect shale anisotropic rock physical model；
4) result of log interpretation and shale anisotropic rock physical model are utilized, by given pore components and clay
The initial model prediction knot of velocity of longitudinal wave, shear wave velocity and density is calculated in the initial value of two parameters of mineral directional index
Fruit；
5) objective function constructed for optimizing shear wave prediction is as shown in formula 1,
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；Deni
For the density of log data actual measurement, Den 'iThe density data calculated for this method；N is total number of samples of log data, and i is sample
Point serial number.
Calculate the square error of log data velocity of longitudinal wave, density and the model calculation, i.e. target function value；
6) when objective function is unsatisfactory for requiring, pore components are updated using Monte Carlo optimization algorithm and clay orients
Index returns to step 4) and repeats above step；
7) when optimization pore components and clay directional index are all unable to get a good prediction result, mesh in any case
It when scalar functions cannot all be met the requirements, returns to step 1) and explanation is optimized to log data, then repeatedly above step.
8) when objective function is met the requirements or reaches maximum number of iterations, terminator operation, the hole obtained by inverting
Gap aspect ratio and clay directional index, utilize anisotropic rock physical model, so that it may the shear wave velocity of prediction be calculated.
9) above-mentioned steps are executed to all well logging dot cycles, shale interval shear wave velocity prediction curve can be obtained.
L-G simulation test verifying is carried out according to the rammell S-Wave Velocity Predicted Method of the present embodiment.Fig. 2 a- Fig. 2 f is Jiao Shi
The log data and result of log interpretation of a bite shale gas well in dam exploratory area, using in the actual measurement velocity of longitudinal wave and Fig. 2 e in Fig. 2 b
Actual density curve as constraint, be based on petrophysical model, utilize Monte Carlo optimization algorithm inverting, Fig. 3 e and Fig. 3 f institute
The clay pore components and clay directional index that inverting optimizes are shown as, Fig. 3 a- Fig. 3 f is with by rammell shear wave speed
Velocity of longitudinal wave (Fig. 3 b), shear wave velocity (Fig. 3 c) and the density curve (Fig. 3 d) for the well that degree prediction technique is predicted are by grey
Curve indicates, it can be seen that the predicted value and measured value of shear wave velocity have good degree of agreement, to demonstrate this method
Application effect.
Compare shortage in current usually shear wave velocity data, therefore to the well of no shear wave velocity curve, passes through the implementation
The shale shear wave prediction technique based on shale anisotropic rock physical model that example is researched and developed, by reservoir hole in modeling process
Gap is divided into brittle mineral hole, clay mineral hole and organic matter hole three parts, has fully considered pore morphology and clay
The directionality of mineral influences, and is anisotropic rock physical model truly, so that modeling result is more true and reliable；
The present invention utilizes Monte Carlo optimization algorithm inverting pore components and clay directional index, and then predicts shear wave velocity, the party
Method is more preferable for domestic strong anisotropy shale formation applicability, and shear wave velocity prediction result is more reasonable and accurate, and institute is pre-
The shear wave velocity and velocity of longitudinal wave good relationship of survey, effect needed for prediction can be reached.To be the prediction of shale gas dessert, storage
The exploration and developments technical research such as layer transformation and monitoring and production application research provide necessary shear wave velocity parameter.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.
Claims (10)
1. a kind of rammell S-Wave Velocity Predicted Method, which is characterized in that this method comprises:
Step 1: acquisition log parameter is explained to log data；
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, it is initial to give porosity aspect ratio
Value and clay mineral directional index initial value；
Step 3: based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale respectively to
Anisotropic petrophysical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet the requirements；
In the case where being unsatisfactory for requirement, pore components and clay mineral directional index are updated by Monte Carlo optimization algorithm,
It repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, it is vertical that inverting obtains porosity
Horizontal when clay mineral directional index, based on porosity, when clay mineral directional index passes through shale anisotropic rock in length and breadth
Physical model obtains prediction shear wave velocity value.
2. rammell S-Wave Velocity Predicted Method according to claim 1, which is characterized in that the step 4 includes:
Square error is calculated by objective function, to the square error given threshold, when square error is greater than the threshold value
It is judged to being unsatisfactory for requiring, is judged to meeting the requirements when the square error is less than or equal to the threshold value；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；DeniTo survey
The density of well data actual measurement, Den 'iThe density data calculated for this method；N is total number of samples of log data, and i is sampling point sequence
Number.
3. rammell S-Wave Velocity Predicted Method according to claim 2, which is characterized in that further include step 5:
To number setting frequency threshold value is determined, when judgement number is more than frequency threshold value, and square error is greater than threshold value, based on survey
Well data optimize explanation, obtain new log parameter, repeat step 2 to step 4.
4. rammell S-Wave Velocity Predicted Method according to claim 3, which is characterized in that further include step 6:
Step 1 is executed to step 5 to all logging points, obtains shale interval shear wave velocity prediction curve.
5. rammell S-Wave Velocity Predicted Method according to claim 1, which is characterized in that building shale anisotropy rock
Stone physical model includes:
Shale matrix is considered as to the mixture of brittle mineral, organic matter and clay composition；
Clay particle is considered as the anisotropic element with the elastic stiffness matrix that immobilizes, introduces clay mineral directional index table
Sign clay mineral aligns degree；
Total pore space is divided into brittleness hole, clay hole and organic matter hole, the addition in brittle mineral hole and organic matter hole uses DEM mould
The addition of type, clay mineral hole uses anisotropy DEM model；
The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, the mixing of clay and mixture 1 using it is each to
Anisotropic SCA-DEM model；
Theory is replaced using Brown-Korringa anisotropic fluid, saturated with fluid page is obtained by dry rock Equivalent Elasticity tensor
Rock Equivalent Elasticity tensor, to set up shale anisotropic rock physical model.
6. a kind of rammell shear wave velocity forecasting system, which is characterized in that the rammell shear wave velocity forecasting system includes:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Step 1: acquisition log parameter is explained to log data；
Step 2: being based on the log parameter, construct shale anisotropic rock physical model, it is initial to give porosity aspect ratio
Value and clay mineral directional index initial value；
Step 3: based on the porosity aspect ratio initial value, the clay mineral directional index initial value and the shale respectively to
Anisotropic petrophysical model obtains velocity of longitudinal wave, shear wave velocity and density；
Step 4: being based on objective function, judge whether the velocity of longitudinal wave, the shear wave velocity and the density meet the requirements；
In the case where being unsatisfactory for requirement, pore components and clay mineral directional index are updated by Monte Carlo optimization algorithm,
It repeats step 3 and recalculates velocity of longitudinal wave, shear wave velocity and density；
In the case where meeting the requirements, it is based on the velocity of longitudinal wave, the shear wave velocity and the density, it is vertical that inverting obtains porosity
Horizontal when clay mineral directional index, based on porosity, when clay mineral directional index passes through shale anisotropic rock in length and breadth
Physical model obtains prediction shear wave velocity value.
7. shear wave velocity forecasting system in rammell according to claim 6, which is characterized in that the step 4 includes:
Square error is calculated by objective function, to the square error given threshold, when square error is greater than the threshold value
It is judged to being unsatisfactory for requiring, is judged to meeting the requirements when the square error is less than or equal to the threshold value；
The objective function are as follows:
Wherein, Vp0iFor the velocity of longitudinal wave of log data actual measurement, V ' p0iThe velocity of longitudinal wave data calculated for this method；DeniTo survey
The density of well data actual measurement, Den 'iThe density data calculated for this method；N is total number of samples of log data, and i is sampling point sequence
Number.
8. shear wave velocity forecasting system in rammell according to claim 7, which is characterized in that further include step 5:
To number setting frequency threshold value is determined, when judgement number is more than frequency threshold value, and square error is greater than threshold value, based on survey
Well data optimize explanation, obtain new log parameter, repeat step 2 to step 4.
9. shear wave velocity forecasting system in rammell according to claim 8, which is characterized in that further include step 6:
Step 1 is executed to step 5 to all logging points, obtains shale interval shear wave velocity prediction curve.
10. shear wave velocity forecasting system in rammell according to claim 9, which is characterized in that building shale anisotropy
Petrophysical model includes:
Shale matrix is considered as to the mixture of brittle mineral, organic matter and clay composition；
Clay particle is considered as the anisotropic element with the elastic stiffness matrix that immobilizes, introduces clay mineral directional index table
Sign clay mineral aligns degree；
Total pore space is divided into brittleness hole, clay hole and organic matter hole, the addition in brittle mineral hole and organic matter hole uses DEM mould
The addition of type, clay mineral hole uses anisotropy DEM model；
The mixing of brittle mineral and organic matter uses isotropism SCA-DEM model, the mixing of clay and mixture 1 using it is each to
Anisotropic SCA-DEM model；
Theory is replaced using Brown-Korringa anisotropic fluid, saturated with fluid page is obtained by dry rock Equivalent Elasticity tensor
Rock Equivalent Elasticity tensor, to set up shale anisotropic rock physical model.
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